Examining latent trajectories of participant engagement in a 12-month eHealth weight management intervention

Objective: Engagement with self-monitoring is crucial for success in digital behavior change interventions for weight loss, but little is known about trajectories of engagement, nor valid predictors of these trajectories. This exploratory trajectory analysis identified engagement patterns based on multiple trajectories of engagement with self-monitoring of weight, diet, and activity in a website-based weight loss intervention over 12 months among adults with overweight/obesity (N = 363). Methods: Latent class growth modeling with a mixture layer used self-monitoring data including number of days tracking weight, diet, and activity on the study website, summed across four 3-month intervals, to identify groups based on engagement trajectories. Regression models examined the association between engagement patterns, demographic variables, and percent weight loss at 12 months. Results: Four engagement patterns emerged: never-engagers (23%), low/declining engagers (48%), early-engagers (13%), and sustained-engagers (16%). Trajectories of engagement were similar across self-monitoring behaviors within the same class. Age, race, and baseline body mass index were associated with likelihood of engagement class membership. Percent weight loss was clinically significant at 12 months for both sustained-engagers (−10.4%) and early-engagers (−5.1%), but not for low/declining (−1.3%) or never-engagers (−0.5%). Conclusion: Promoting early self-monitoring engagement may be of equal or greater importance than promoting sustained engagement to achieve desired weight loss outcomes in a digital behavior change intervention for weight loss. Given the high proportion of low/declining engagers who did not achieve clinically significant weight losses, there is a need to characterize and identify these participants early on to promote engagement with self-monitoring.